arbiter
JournalsPricingAccount

AI-enabled smart retails for understanding in-store customer journeys and classifying different types of customers

Jongsawas Chongwatpol

Journal of Business Analytics2026https://doi.org/10.1080/2573234x.2026.2645971article
AJG 1ABDC C
Weight
0.50

What the paper says

No abstract available.

Open paper page →

Cite this paper

https://doi.org/https://doi.org/10.1080/2573234x.2026.2645971

Or copy a formatted citation

@article{jongsawas2026,
  title        = {{AI-enabled smart retails for understanding in-store customer journeys and classifying different types of customers}},
  author       = {Jongsawas Chongwatpol},
  journal      = {Journal of Business Analytics},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1080/2573234x.2026.2645971},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

AI-enabled smart retails for understanding in-store customer journeys and classifying different types of customers

Flags are reviewed by the Arbiter methodology team within 5 business days.

Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.